Field
This disclosure provides techniques for rendering images of scenes including three-dimensional virtual geometry.
Description of the Related Art
Rendering is the automated process of generating photorealistic or nonphotorealistic images from two or three-dimensional models. Monte Carlo rendering techniques have been used to simulate light propagation by sampling random paths connecting a light source and a virtual sensor. In scenes with complex materials, geometry, or lighting, the space of light paths can be large and high-dimensional, while the subset of paths contributing significantly to the rendered image may occupy only a narrow subspace. This can make Monte Carlo rendering a difficult sampling problem.
In contrast to traditional Monte Carlo rendering techniques, Markov Chain Monte Carlo (MCMC) rendering techniques, such as Metropolis Light Transport (MLT), generate a statistically dependent sequence of samples (light paths) with a density proportional to a non-negative function, typically using the Metropolis-Hastings steps, drawing a proposal state from a proposal distribution which is accepted with a certain probability to become the next state of the Markov Chain (with the process repeating anew if the proposal is not accepted). Primary Sample Space MLT (PSSMLT) retrofits such Metropolis sampling to traditional Monte Carlo techniques by treating them as abstract path samplers and perturbing the random numbers they consume. Multiplexed MLT (MMLT) further allows the Markov Chain to adaptively select the bidirectional sampling techniques that have high contribution. However, operating in the space of random numbers can make these techniques less successful at locally exploring important regions of the state space. For example, since most sampling schemes construct paths incrementally, a PSSMLT change in the random numbers used by one vertex on the path generally leads to a ripple change that changes the path geometry by affecting all subsequent vertices, and the changing of sampling techniques in MMLT means the random numbers are reinterpreted as input to a different technique, producing an entirely different path. Such changes in the path geometry can in turn lead to increased amounts of noise and undesirable noise distributions in rendered images, among other things.